Machine learning and landslide studies: recent advances and applications
Upon the introduction of machine learning (ML) and its variants, in the form that we know
today, to the landslide community, many studies have been carried out to explore the …
today, to the landslide community, many studies have been carried out to explore the …
[HTML][HTML] Applications of machine learning methods for engineering risk assessment–A review
The purpose of this article is to present a structured review of publications utilizing machine
learning methods to aid in engineering risk assessment. A keyword search is performed to …
learning methods to aid in engineering risk assessment. A keyword search is performed to …
A generalized method to predict the compressive strength of high-performance concrete by improved random forest algorithm
Q Han, C Gui, J Xu, G Lacidogna - Construction and Building Materials, 2019 - Elsevier
The prediction results of high-performance concrete compressive strength (HPCCS) based
on machine learning methods are seriously influenced by input variables and model …
on machine learning methods are seriously influenced by input variables and model …
Landslide displacement forecasting using deep learning and monitoring data across selected sites
Accurate early warning systems for landslides are a reliable risk-reduction strategy that may
significantly reduce fatalities and economic losses. Several machine learning methods have …
significantly reduce fatalities and economic losses. Several machine learning methods have …
[HTML][HTML] Forecasting the time of failure of landslides at slope-scale: A literature review
Forecasting the time of failure of landslides at slope-scale is a difficult yet important task that
can mitigate the effects of slope failures in terms of both human lives and economic losses …
can mitigate the effects of slope failures in terms of both human lives and economic losses …
Pathways and challenges of the application of artificial intelligence to geohazards modelling
The application of artificial intelligence (AI) and machine learning in geohazard modelling
has been rapidly growing in recent years, a trend that is observed in several research and …
has been rapidly growing in recent years, a trend that is observed in several research and …
Machine learning ensemble modelling as a tool to improve landslide susceptibility mapping reliability
Statistical landslide susceptibility mapping is a topic in complete and constant evolution,
especially since the introduction of machine learning (ML) methods. A new methodological …
especially since the introduction of machine learning (ML) methods. A new methodological …
Machine learning for landslides prevention: a survey
Landslides are one of the most critical categories of natural disasters worldwide and induce
severely destructive outcomes to human life and the overall economic system. To reduce its …
severely destructive outcomes to human life and the overall economic system. To reduce its …
[HTML][HTML] Formulation of estimation models for the compressive strength of concrete mixed with nanosilica and carbon nanotubes
New concepts for improving the performance of cementitious materials have recently
surfaced due to the advancement in nanotechnology. In this context, nano silica (NS) and …
surfaced due to the advancement in nanotechnology. In this context, nano silica (NS) and …
Low-cost sensor-based and LoRaWAN opportunities for landslide monitoring systems on IoT platform: a review
Landslides are a frequent natural hazard during the rainy season, causing infrastructural
and economic damage globally. Several studies on landslide monitoring techniques have …
and economic damage globally. Several studies on landslide monitoring techniques have …